Best Practices for Converting 1990 Blocks to 2010 Census Tracts and Handling Median Values

NHGIS
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  • Can I apply the interpolation weights provided by NHGIS in the same way?

I see no conceptual issues with your proposal. It should work the same for block-level medians as it does for tract-level medians, and in fact, starting from block-level medians would produce more accurate results. (As I understand, your method basically works on an assumption that all census responses within a source zone have a characteristic equal to the zone’s median–e.g., all people in a source tract have an age equal to the tract’s median age–and this assumption should be more accurate for block-level medians. Individual blocks have much smaller populations than tracts, so block-level medians should better correspond to individual-level characteristics than tract-level medians.)

  • How should I approach collapsing and unweighting the block-level data?

You could use the same workflow that you describe for tract-to-tract crosswalks and just replace the tract-to-tract crosswalk with an NHGIS block-to-tract crosswalk. The NHGIS website provides these general instructions for using the block crosswalks, and these instructions roughly mirror how you’ve described your process for tract-to-tract allocations. If that’s still not clear, please let me know.

  • Are there any key differences or considerations when working with block-level data for medians?

The biggest issue is that, to my knowledge, the 1990 census summary files didn’t provide medians for blocks, and no source provides “long-form data” (covering income, education, marital status, nativity, etc.) for blocks.

For long-form data, you’d need to start from block groups, block group parts, or census tracts, as explained in this section of the Crosswalks page.

For medians of 1990 short-form characteristics (like median age), you could still use block-level data, but you wouldn’t be able to start directly with a median statistic. Instead, you could use one of the two strategies I suggested in this earlier forum post, which I’ve copied here:

  1. Use means instead of medians, and apply crosswalks separately for each mean’s numerator and denominator. E.g., to compute per capita income, you could estimate “aggregate income” and “total population” separately using the crosswalk weights, and then divide one by the other.
  2. Start with a table of counts broken down by the value of interest, e.g., housing units by home value, and use the crosswalk to estimate each count in the table. Then estimate the median from the frequency distribution, for which there are various online guides .
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